Mental health research: Larger studies are needed
Researchers have recently found that some studies on mental illness are not broad enough to provide reliable data. To collect more reliable and consistent data on how mental illness behaves in the brain, studies need to include a sample size of thousands of brains, according to a study published in Nature.
About the study: In this study, the researchers conducted an analysis of several other mental health studies – including about 50,000 brains – and found some differences between data collected in smaller studies and larger studies on the same topic.
MRI examinations: The main study found that data from MRI scans is far more accurate than other methods of assessing mental illness, such as mental illness. B. Questionnaires. The best way to get accurate data is with an MRI, which isn’t always accessible.
- One issue with performing MRI scans is cost. MRIs can total about $1,000 an hour, which can stand in the way of using larger sample sizes, the study said.
The problem with small sample sizes: Many small mental health studies have pulled data from sample sizes as small as 25 people. It is becoming increasingly clear in the neuroscience community that thousands of brains are required for accurate data.
- The study states: “Small studies are most susceptible to sample variability, the random variation of an association between subsamples of the population. Sample variability decreases and associations stabilize with increasing sample size.”
- When a smaller study has confirmed a finding, scientists recommend verifying that data with a larger study.
- Small studies can only highlight brain features normally associated with mood, behavior or mental abilities, not mental illness, according to NPR’s coverage of the study.
Why larger studies are needed: Differences in the brain that indicate mental illness are less obvious and more controversial, according to NPR. Larger studies are needed to ensure the data is being tracked across a wide range of different brains.
- When small studies were conducted, an area of the brain or connection that appeared important in one set of scans sometimes seemed insignificant in another.
- As the sample size increased to thousands of brains, the results became more reliable, according to NPR.
Publication bias: Several small studies are likely to come to similar, apparently significant, conclusions. This can sometimes lead the general public to think that these results are “conventional wisdom” when in reality the data is incomplete and often misleading. NPR states that this is known as publication bias.
- When larger studies are conducted, it’s much more difficult to reach the same conclusions, which NPR says can lead to inconsistencies in the data based on study size.